Software defects prediction at the initial period of the software development life cycle remains a critical and important assignment. Defect prediction and correctness leads to the assurance of the quality of software systems and has remained integral to study in the previous years. The quick forecast of imperfect or defective modules in software development can serve the development squad to use the existing assets competently and effectively to provide remarkable software products in a given short timeline. Hitherto, several researchers have (...) industrialized defect prediction models by utilizing statistical and machine learning techniques that are operative and effective approaches to pinpoint the defective modules. Tree family machine learning techniques are well-thought-out to be one of the finest and ordinarily used supervised learning methods. In this study, different tree family machine learning techniques are employed for software defect prediction using ten benchmark datasets. These techniques include Credal Decision Tree, Cost-Sensitive Decision Forest, Decision Stump, Forest by Penalizing Attributes, Hoeffding Tree, Decision Tree, Logistic Model Tree, Random Forest, Random Tree, and REP-Tree. Performance of each technique is evaluated using different measures, i.e., mean absolute error, relative absolute error, root mean squared error, root relative squared error, specificity, precision, recall, F-measure, G-measure, Matthew’s correlation coefficient, and accuracy. The overall outcomes of this paper suggested RF technique by producing best results in terms of reducing error rates as well as increasing accuracy on five datasets, i.e., AR3, PC1, PC2, PC3, and PC4. The average accuracy achieved by RF is 90.2238%. The comprehensive outcomes of this study can be used as a reference point for other researchers. Any assertion concerning the enhancement in prediction through any new model, technique, or framework can be benchmarked and verified. (shrink)

A passive brain–computer interface based upon functional near-infrared spectroscopy brain signals is used for earlier detection of human drowsiness during driving tasks. This BCI modality acquired hemodynamic signals of 13 healthy subjects from the right dorsolateral prefrontal cortex of the brain. Drowsiness activity is recorded using a continuous-wave fNIRS system and eight channels over the right DPFC. During the experiment, sleep-deprived subjects drove a vehicle in a driving simulator while their cerebral oxygen regulation state was continuously measured. Vector phase analysis (...) was used as a classifier to detect drowsiness state along with sleep stage-based threshold criteria. Extensive training and testing with various feature sets and classifiers are done to justify the adaptation of threshold criteria for any subject without requiring recalibration. Three statistical features along with six VPA features were used. The average accuracies for the five classifiers are 90.9% for discriminant analysis, 92.5% for support vector machines, 92.3% for nearest neighbors, 92.4% for both decision trees, and ensembles over all subjects’ data. Trajectory slopes of CORE vector magnitude and angle: m and m are the best-performing features, along with ensemble classifier with the highest accuracy of 95.3% and minimum computation time of 40 ms. The statistical significance of the results is validated with a p-value of less than 0.05. The proposed passive BCI scheme demonstrates a promising technique for online drowsiness detection using VPA along with sleep stage classification. (shrink)

The Belt and Road initiative was announced in 2013 under the administration of China’s President, Xi Jinping. It was designed to fulfill the aim of interconnecting Asia, Europe, and Africa through reliable connectivity networks. In reaction to it, the 47th summit of G7 in June 2021 has given a response to this Chinese Initiative with the idea of Build Back Better World. G7 tried to show that the world can have an alternative to BRI. The main objective of the study (...) is to compare the feasibility of these two massive infrastructural projects. It is a qualitative document analysis of the previously published material on the related theme, that highlighted a competition of economic supremacy between the US and China. The research finds that BRI is gaining enough popularity as compared to B3W in the eyes of the world specifically in connecting different regions. (shrink)

_The Belt and Road initiative was announced in 2013 under the administration of China’s President, Xi Jinping. It was designed to fulfill the aim of interconnecting Asia, Europe, and Africa through reliable connectivity networks. In reaction to it, the 47 th summit of G7 in June 2021 has given a response to this Chinese Initiative with the idea of Build Back Better World (B3W). G7 tried to show that the world can have an alternative to BRI. The main objective of (...) the study was to compare the feasibility of these two massive infrastructural projects. It is a qualitative document analysis of the previously published material on the related theme, that highlighted a competition of economic supremacy between the US and China. The research found that BRI was gaining enough popularity as compared to B3W in the eyes of the world specifically in connecting different regions._. (shrink)

Drawing on social cognitive theory and social information processing theory, this study investigated how organizations' efforts to embody environmental corporate social responsibility (ECSR) shape consumer perception of a green corporate image through employees' environmental passion and pro-environmental behavior (PEB). To test our hypotheses, we collected multisource time-lagged data from 214 employee–customer dyads from hotel and banking sector organizations in Pakistan. The findings show that organizations' green corporate image is a function of their efforts to engage in ECSR activities as demonstrated (...) through employees' environmental passion and PEB. These findings have important implications in the environment and management domains because it can help organizations draft useful strategies to counter environmental degradation and generate a green corporate image in customers' minds through employees' green behavior. (shrink)

This study aims to examine the underlying mechanism of the relationship between perceived green human resource management and perceived employee green behavior. By drawing on attitude and social exchange theories, we examined green commitment as a mediator and green knowledge sharing as a moderator of the GHRM–EGB relationship. The study employs partial least square structural equation modeling to analyze 329 responses. Data were collected in two time lags. The empirical results confirmed that GC mediates the relationship between GHRM and EGB. (...) However, the study results found that GKS moderated the indirect influence of GHRM on green behavior via GC. This research signifies the effect of GHRM, GKS, GC, and green behavior on organizations’ sustainability and environmental management. Despite the emerging literature on the significance of green practices in organizations for environmental management, no study has examined the moderating role of GKS on the indirect effect of GHRM on green behavior via mediating role of GC. This study offers valuable insight into environmental management in organizations through green practices and green behavior. (shrink)

Nature-inspired optimization techniques are useful tools in electrical engineering problems to minimize or maximize an objective function. In this paper, we use the firefly algorithm to improve the optimal solution for the problem of directional overcurrent relays (DOCRs). It is a complex and highly nonlinear constrained optimization problem. In this problem, we have two types of design variables, which are variables for plug settings (PSs) and the time dial settings (TDSs) for each relay in the circuit. The objective function is (...) to minimize the total operating time of all the basic relays to avoid unnecessary delays. We have considered four models in this paper which are IEEE (3-bus, 4-bus, 6-bus, and 8-bus) models. From the numerical results, it is obvious that the firefly algorithm with certain parameter settings performs better than the other state-of-the-art algorithms. (shrink)

Nowadays, online product reviews have been at the heart of the product assessment process for a company and its customers. They give feedback to a company on improving product quality, planning, and monitoring its business schemes in order to increase sale and gain more profit. They are also helpful for customers to select the right products in less effort and time. Most companies make spam reviews of products in order to increase the products sales and gain more profit. Detecting spam (...) product reviews is a challenging issue in NLP. Numerous machine learning approaches have attempted to detect and classify the product reviews as spam or nonspam. However, in order to improve the classification accuracy, this study has introduced an ensemble machine learning model that combines predictions from multilayer perceptron, K-Nearest Neighbour, and Random Forest and predicts the outcome of the review as spam or real, based on the majority vote of the contributing models. In order to accomplish the task of spam review classification, the proposed ensemble and other benchmark boosting approaches are tested with 25 statistical features extracted from mobile application reviews of Yelp Dataset. Then, three different selection techniques are exploited to diminish the feature space and filter out the top 10 optimal features. The effectiveness of the proposed ensemble, the individual models, and other benchmark boosting approaches is again evaluated with 10 optimal features in terms of classification accuracy. Experimental outcomes illustrate that the proposed ensemble model outperformed the individual classifiers and state-of-the-art boosting approaches like Generalized Boost Regression Model, Extreme Gradient Boost, and AdaBoost Regression Model in terms of classification accuracy. (shrink)

This work identifies the influence of chaos theory on fractional calculus by providing a theorem for the existence and stability of solution in fractional-order gyrostat model with the help of a fixed-point theorem. We modified an integer order gyrostat model consisting of three rotors into fractional order by attaching rotatory fuel-filled tank and provided an iterative scheme for our proposed model as a working rule of obtained analytical results. Moreover, this iterative scheme is injected into algorithms for a system of (...) integer order dynamical systems to observe Lyapunov exponents and a bifurcation diagram for our proposed fractional-order dynamical model. Furthermore, we obtained five equilibrium points, including four unstable spirals and one saddle node, using local dynamical analysis which acted as self-exciting attractors and a separatrix in a global domain. (shrink)

The Indonesian Ulema Council (MUI) has issued an illegitimate fatwa against smoking in mosques because it endangers the health of worshippers and interferes with the comfort of worshippers. This study aims to investigate smoking behaviour in mosques and violations of fatwas from ulama and governor regulations. This study follows a cross-sectional design conducted by interviewing 531 Muslims who have prayed in the mosque for the last 14 days and observed the compliance of the mosque in implementing a smoke-free policy in (...) 315 mosques. Frequency distribution and cross-tabulation were carried out using JASP 16 software using cross-tabulation. The results of this study indicate that the implementation of the smoke-free policy for mosques in Medan has been violated many times (57.8%), especially the violation regarding smoking in mosques (32.1%); cigarette butts were still found in the yard of the mosque (44.1%). Violations of the policy of fatwa smoke-free areas occurred in public mosques (61%) and muhammadiyah mosques (46.5%). Smoking behaviour in mosques was seen in the last 2 weeks, namely smoking behaviour carried out by worshippers (57.6%), smoking behaviour carried out by mosque administrators (39.2%), smoking behaviour carried out by community leaders in mosques (19.4%) and smoking behaviour that ulemas carried out in mosques (14.3%). Worshippers must comply with the rules against smoking in mosques because it can endanger the health of other worshippers. Cigarette smoke in the mosque will make other worshippers uncomfortable to worship so that it can damage the solemnity of the congregation to worship in the mosque. Contribution: This study is expected to explain smoking behaviour in mosques, violations of smoking behaviour in mosques that violate the ulama’s fatwa regarding smoking behaviour in mosques and the governor’s regulation on smoking behaviour in mosques. (shrink)

The aim of the study is to reveal the underlying structure of issues of university students taking online classes during the COVID-19 pandemic period. The overall design of the study includes a review of contemporary literature and field survey for data collection and analysis. Discourse of literature coupled with expert opinion has been employed for identification of issues. Interpretive Structural Modeling is used for the determination of intra-issue relationships and analyzing the underlying structure. Cross impact matrix multiplication applied to classification (...) is used as a technique for classifying issues on the basis of driving–dependence power. Results of the literature show that there are 21 major issues faced by the students taking online classes. ISM shows that lack of institutional guidelines, lack of regulators’ guidelines, stress of pandemic situation, and abrupt start of online classes are the most critical issues. MICMAC analysis reveals that there is no autonomous issue, 4 are independent, 6 other issues are dependent, and the remaining 11 are linking. This is a valuable study having practical implications for regulators, students, parents, and society to understand the current problem. It is an original attempt that contributes toward literature in the form of a structural model and a diagram of classification of issues. (shrink)

Text and Context: Quran and Contemporary Challenges is a compilation of Arif Mohammed Khan s thought-provoking articles published in various newspapers and magazines. It is a comprehensive understanding of the Message and Spirit of Quran and Prophetic Tra.

This study examined the influence of ethical leadership on knowledge sharing, the mediating role of psychological ownership, and the moderating effect of professional commitment between ethical leadership and knowledge sharing. Data were collected from 307 public listed Pakistani companies’ employees. Statistical analyses were performed by using SPSS Version 25 and AMOS version 22. The findings indicate a positive relationship between EL and KS behavior. Additionally, the impact of EL on KS was partially mediated by psychological ownership. Furthermore, professional commitment buffers (...) the link between EL and KS. This study contributes to the body of knowledge in the field of leadership by confirming the role of ethics. The results show that ethical leaders develop employee attitudes that contribute to employee KS behavior. Ethical leaders create and encourage a learning culture to enhance organizational performance. This study adds to the little data on the positive impact of EL on listed company’s employees and addresses the gaps in previous studies on the role of EL in changing environments. In addition, professional commitment as a moderator has not been previously investigated with ethical leadership antecedents. (shrink)

If one thing that the failed coup by a small but some of the top hierarchy of Turkish armed forces on that fateful July 15, 2016 day made clear, it was: the ordinary civilians, unarmed as they were poured into the streets to defend the government whatever way they can. This massive public sympathy and support for Turkish resident Erdogan and his government would be hard, if not impossible to understand, without knowing the historical intellectual, academic, and moral combat between (...) the modernists and Islamist groups working within the country. Mustafa Kamal had turned Turkey, mostly by force, from Ottoman Empire into the secular mode using military power. Various Islamic revolutionary outfits struggled for the revival of Ottoman Empire. Among them Bedi-uz-Zaman Said Nursi managed to cast a strong influence. A little slow but steadfast effort influenced by Nursi movement. Islam-shy Western powers managed alternate power structure against sitting President Tayyep Erdogan. They, however, failed due to result oriented social work delivered by his regime as Mayor and Prime Minister. It is a lesson for other revolutionaries and Governments especially for Islamic revolutionaries that if politicians deliver no power can oust them like a bee from butter. (shrink)

Using a time-lagged design, we tested the main effects of Islamic Work Ethic (IWE) and perceived organizational justice on turnover intentions, job satisfaction, and job involvement. We also investigated the moderating influence of IWE in justice–outcomes relationship. Analyses using data collected from 182 employees revealed that IWE was positively related to satisfaction and involvement and negatively related to turnover intentions. Distributive fairness was negatively related to turnover intentions, whereas procedural justice was positively related to satisfaction. In addition, procedural justice was (...) positively related to involvement and satisfaction for individuals high on IWE however it was negatively related to both outcomes for individuals low on IWE. For low IWE, procedural justice was positively related to turnover intentions, however it was negatively related to turnover intentions for high IWE. In contrast, distributive justice was negatively related to turnover intentions for low IWE and it was positively related to turnover intentions for high IWE. (shrink)

The current study investigates whether tournament incentives motivate chief executive officer to be socially responsible. Furthermore, it explores the role of sub-national institutional contingencies [i.e., state-owned enterprises vs. non-SOEs, foreign-owned entities vs. non-FOEs, cross-listed vs. non-cross-listed, developed region] in CEO tournament incentives and the corporate social responsibility performance relationship. Data were collected from all A-shared companies listed in the stock exchanges of China from 2014 to 2019. The study uses the baseline methodology of ordinary least squares and cluster OLS regression. (...) Moreover, firm-fixed effects regression, two-stage least squares regression, and propensity score matching deal with the endogeneity problem and check the robustness of the results. The results provide reliable evidence that tournament incentives motivate CEOs to be more socially responsible. On the other hand, sub-national institutional contingencies positively affect the association between CEO tournament incentives and CSRP. The findings have important implications for companies and regulators who wish to enhance CSP by providing incentives to top managers. (shrink)

The novel coronavirus (COVID-19) has imperatively shaken the behavior of the global financial markets. This study estimated the impact of COVID-19 on the behavior of the financial markets of Europe and the US. The results revealed that the returns of the S&P 500 index have been greatly affected by a lockdown in the US owing to COVID-19. However, the health crisis generated due to the novel coronavirus significantly decreased the stock returns of the Nasdaq Composite index. The results also showed (...) that the economic crisis generated from the pandemic in Spain has had more impact on the IBEX 35 as compared to the health crisis itself. On the other hand, in the long-run, Italy’s stock markets are more affected by the health crisis as contrasted with the economic crisis, while, in the short-run, both lockdown conditions and economic instability lower the stock returns of FTSE MIB. The UK stock markets witnessed that in the short-run, deficiency of health management systems imperatively damaged the stock returns of the London Stock Exchange. The investigation revealed that deficiency of health systems and lockdown conditions have imperatively damaged the structure of financial markets, inferring that sustainable development of these nations is at risk due to COVID-19. The study suggested that governments should allocate more of their budget to the health sector to overcome a health crisis in the future. (shrink)

Synthesizing theories of ethical leadership, psychological climate, pro-environmental behavior, and gender, first, we proposed and tested a model linking supervisors’ ethical leadership and organizational environmental citizenship behavior via green psychological climate. Then we tested the moderating effect of gender on the indirect (via green psychological environment) relationship between supervisors’ ethical leadership and organizational environmental citizenship behavior. Time-lagged (three waves, two months apart) survey data were collected from 447 employees in various manufacturing and service sector firms operating in China. Data were (...) analyzed using structural equation modeling, bootstrapping, and multi-group technique to test the hypothesized relationships. The results showed a positive relationship between employee ratings of supervisors’ ethical leadership and organizational environmental citizenship behavior. Moreover, green psychological climate mediates the relationship between supervisors’ ethical leadership and organizational environmental citizenship behavior. Importantly, the multi-group analysis revealed that gender moderates the indirect relationship (via green psychological climate) between supervisors’ ethical leadership and organizational environmental citizenship behavior. The study carries useful practical implications for policymakers and managers concerned about environmental sustainability. (shrink)

Jensen’s inequality is one of the fundamental inequalities which has several applications in almost every field of science. In 2003, Mercer gave a variant of Jensen’s inequality which is known as Jensen–Mercer’s inequality. The purpose of this article is to propose new bounds for Csiszár and related divergences by means of Jensen–Mercer’s inequality. Also, we investigate several new bounds for Zipf–Mandelbrot entropy. The idea of this article may further stimulate research on information theory with the help of Jensen–Mercer’s inequality.

This study aims to investigate the impact of stakeholders’ views on the practices of green innovation, consequent effect on environmental and organizational performance, and moderating influence of innovation orientation. A quantitative method was employed for the sample size of 515 responses. To accumulate the data from the respondents, convenient random sampling was used. Data were collected from manufacturing and services firms through a field survey by using a closed-ended questionnaire based in the Punjab province of Pakistan. The analysis was done (...) using the structural equation model of the partial least square analysis method. Our findings proved a positive and significant link between stakeholders’ views on GI practices. A significant association has been found between GI practices and environmental and OP. The moderating effect was found to be negative but statistically significant. This research offers numerous contributions and provides decision-making insinuations. (shrink)

During the COVID-19 outbreak, educational institutions were closed, and students worldwide were confined to their homes. In an educational environment, students depend on collaborative learning to improve their learning performance. This study aimed to increase the understanding of social media adoption among students during the COVID-19 pandemic for the purpose of CL. Social media provides a learning platform that enables students to easily communicate with their peers and subject specialists, and is conducive to students' CL. This study addresses the key (...) concept of CL during the COVID-19 pandemic by assessing social media use among students in higher education. The relationship between social media use and students' performance is crucial to understanding the role of social media during a pandemic. This study is based on constructivism theory and the technology acceptance model. Structural equation modeling was used to analyze the conceptual model using SmartPLS. The research findings indicate that social media plays an important role during the pandemic because it provides opportunities for students to enhance CL under the aforementioned situations. This study makes noteworthy theoretical and practical contributions. (shrink)

Half a million species of plants could be existing in the world. Classification of plants based on leaf features is a critical job as feature extraction from binary images of leaves may result in duplicate identification. However, leaves are an effective means of differentiating plant species because of their unique characteristics like area, diameter, perimeter, circularity, aspect ratio, solidity, eccentricity, and narrow factor. This paper presents the extraction of plant leaf gas alongside other features from the camera images or a (...) dataset of images by applying a convolutional neural network. The extraction of leaf gas enables identification of the actual level of chlorophyll and nitrogen which may help to interpret future predictions. Our contribution includes the study of texture and geometric features, analyzing ratio of Ch and N in both healthy and dead leaves, and the study of color-based methods via CNN. Several steps are included to obtain the results: image preprocessing, testing, training, enhancement, segmentation, feature extraction, and aggregation of results. A vital contrast of the results can be seen by considering the kind of image, whether a healthy or dead leaf. (shrink)

Social media plays a significant role in modern life, but excessive use of it during the COVID-19 pandemic has become a source of concern. Supported by the conservation of resources theory, the current study extends the literature on problematic social media usage during COVID-19 by investigating its association with emotional and mental health outcomes. In a moderated mediation model, this study proposes that problematic social media use by workers during COVID-19 is linked to fear of COVID-19, which is further associated (...) with depression. The current study tested trait mindfulness as an important personal resource that may be associated with reduced fear of COVID-19 despite problematic social media use. The study collected temporally separate data to avoid common method bias. Pakistani employees working in different organizations completed a series of survey questionnaires. The results supported the moderated mediation model, showing that problematic social media use during the current pandemic is linked to fear of COVID-19 and depression among employees. Furthermore, trait mindfulness was found to be an important buffer, reducing the negative indirect association between problematic social media use and depression through fear of COVID-19. These results offer implications for practitioners. The limitations of this study and future research directions are also discussed. (shrink)

Our objective is to examine the effects of Big Five personality traits on ethical ideologies using a time-lagged design of 406 employees of higher education institutions in Pakistan. Based on low/high idealism versus relativism, we investigate the conceptual linkage between each of the personality traits and moral philosophy. The results illustrate that extraversion and openness to experience believed on subjectivism moral philosophy, agreeableness believed on situationism, and neuroticism believed on absolutism moral philosophies. In addition, contentiousness believed on exceptionism moral philosophy. (...) Furthermore, managerial implications and future research directions are suggested. (shrink)

Cardiac disease is the leading cause of death worldwide. Cardiovascular diseases can be prevented if an effective diagnostic is made at the initial stages. The ECG test is referred to as the diagnostic assistant tool for screening of cardiac disorder. The research purposes of a cardiac disorder detection system from 12-lead-based ECG Images. The healthcare institutes used various ECG equipment that present results in nonuniform formats of ECG images. The research study proposes a generalized methodology to process all formats of (...) ECG. Single Shoot Detection MobileNet v2-based Deep Neural Network architecture was used to detect cardiovascular disease detection. The study focused on detecting the four major cardiac abnormalities with 98% accuracy results were calculated. The work is relatively rare based on their dataset; a collection of 11,148 standard 12-lead-based ECG images used in this study were manually collected from health care institutes and annotated by the domain experts. The study achieved high accuracy results to differentiate and detect four major cardiac abnormalities. Several cardiologists manually verified the proposed system’s accuracy result and recommended that the proposed system can be used to screen for a cardiac disorder. (shrink)

We examined a largely ignored but imperative dimension of safety literature by testing the impact of ethical leadership style on organizational safety performance. We also tested dual mediating paths of safety culture and safety consciousness in the relationship between ethical leadership style and organizational safety consciousness. Data were collected from a large public sector telecom company in Pakistan. Confirmatory factor analysis was used to assess the reliability and validity of the study scales and model fit. Preacher and Hayes’s macro of (...) mediation was employed to test the direct and indirect paths proposed in the study. The findings suggest that ethical leadership has a positive impact on organizational safety performance. Partial mediating roles of safety culture and safety consciousness were also found between the dependent and independent variables. Theoretical and practical implications are discussed. (shrink)

Substance use disorders (SUDs) constitute a growing global health crisis, yet many limitations and challenges exist in SUD treatment research, including the lack of objective brain-based markers for tracking treatment outcomes. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity, and although much is known about EEG activity in acute and chronic substance use, knowledge regarding EEG in relation to abstinence and treatment outcomes is sparse. We performed a scoping review of longitudinal and pre-post treatment EEG studies that explored (...) putative changes in brain function associated with abstinence and/or treatment in individuals with SUD. Following PRISMA guidelines, we identified studies published between January 2000 and March 2022 from online databases. Search keywords included EEG, addictive substances (e.g., alcohol, cocaine, methamphetamine), and treatment related terms (e.g., abstinence, relapse). Selected studies used EEG at least at one time point as a predictor of abstinence or other treatment-related outcomes; or examined pre- vs. post-SUD intervention (brain stimulation, pharmacological, behavioral) EEG effects. Studies were also rated on the risk of bias and quality using validated instruments. Forty-four studies met the inclusion criteria. More consistent findings included lower oddball P3 and higher resting beta at baseline predicting negative outcomes, and abstinence-mediated longitudinal decrease in cue-elicited P3 amplitude and resting beta power. Other findings included abstinence or treatment-related changes in late positive potential (LPP) and N2 amplitudes, as well as in delta and theta power. Existing studies were heterogeneous and limited in terms of specific substances of interest, brief times for follow-ups, and inconsistent or sparse results. Encouragingly, in this limited but maturing literature, many studies demonstrated partial associations of EEG markers with abstinence, treatment outcomes, or pre-post treatment-effects. Studies were generally of good quality in terms of risk of bias. More EEG studies are warranted to better understand abstinence- or treatment-mediated neural changes or to predict SUD treatment outcomes. Future research can benefit from prospective large-sample cohorts and the use of standardized methods such as task batteries. EEG markers elucidating the temporal dynamics of changes in brain function related to abstinence and/or treatment may enable evidence-based planning for more effective and targeted treatments, potentially pre-empting relapse or minimizing negative lifespan effects of SUD. (shrink)

Recently the World Health Organization has highlighted the need to strengthen mental health systems following emergencies, including natural and manmade disasters. Mental health services need to be informed by culturally attuned evidence that is developed through research. Therefore, there is an urgent need to establish rigorous ethical research practice to underpin the evidence-base for mental health services delivered during and following emergencies.

Bound-constrained optimization has wide applications in science and engineering. In the last two decades, various evolutionary algorithms were developed under the umbrella of evolutionary computation for solving various bound-constrained benchmark functions and various real-world problems. In general, the developed evolutionary algorithms belong to nature-inspired algorithms and swarm intelligence paradigms. Differential evolutionary algorithm is one of the most popular and well-known EAs and has secured top ranks in most of the EA competitions in the special session of the IEEE Congress on (...) Evolutionary Computation. In this paper, a customized differential evolutionary algorithm is suggested and applied on twenty-nine large-scale bound-constrained benchmark functions. The suggested C-DE algorithm has obtained promising numerical results in its 51 independent runs of simulations. Most of the 2013 IEEE-CEC benchmark functions are tackled efficiently in terms of proximity and diversity. (shrink)

With the development of wireless technology, two basic wireless network models that are commonly used, known as infrastructure and wireless ad hoc networks, have been developed. In the literature, it has been observed that channel contention is one of the main reasons for packet drop in WANETs. To handle this problem, this paper presents a routing protocol named CCBR. CCBR tries to determine a least contended path between the endpoints to increase packet delivery ratio and to reduce packet delay and (...) normalized routing overhead. Moreover, throughout the active data section, each intermediate node computes its channel contention value. If an intermediate node detects an increase in channel contention, it notifies the source node. Then the source node determines another least contended route for transmission. The advantages of CCBR are verified in our NS2-based performance study, and the results show that CCBR outperforms ad hoc on-demand distance vector in terms of packet delivery ratio, end-to-end delay, and routing overhead by 4% to 9%. (shrink)

This study sheds light on strategies for retaining skilled pharmacists in Pakistan's pharmaceutical sector, offering valuable insights for both academia and industry stakeholders by investigating the impact of human resource management practices, including training and development, compensation and rewards, job performance, and job satisfaction, on employee retention. It also examines the moderating role of career growth in this context. Theoretical foundations are grounded in international migration theories and social exchange theory, providing a comprehensive framework for the study. A cross-sectional survey (...) design was used to collect data from 254 pharmacists in southern Punjab, Pakistan. Structural equation modeling (SEM) was employed for data analysis. Findings reveal that training and development, compensation and rewards, job performance, and job satisfaction all have significant direct effects on employee retention. Additionally, career growth acts as a crucial moderator, strengthening the relationship between training and development and job performance, as well as compensation and rewards and job satisfaction in relation to employee retention. Theoretical implications emphasize the importance of tailored training programs, fair compensation practices, and career growth opportunities. Practical recommendations include creating a positive work environment, rewarding high-performing employees, and fostering career development. Future research directions encompass longitudinal studies, the influence of organizational culture and technology, regional variations, and additional factors affecting retention. (shrink)

Internet of Things-based environments pose various challenges due to their anytime/anywhere computing, and the efficient cryptographic based key management is one of the major challenges in Internet of Things. The key management life cycle consists of initialization, key generation, key registration, key backup, key update, key recovery, and key revocation. Our contribution in this paper is to summarize the state-of-the-art key management schemes and techniques in different scenarios, such as mobile ad hoc networks, wireless sensor networks, and the Internet of (...) Things environments. Further different issues related specifically to the Internet of Things environment are discussed and the causes and effects pertaining to the security breach for Internet of Things are identified. Furthermore, in this research work, we develop a novel permutation of threshold and identity-based key management schemes for the Internet of Things environment and have proposed future directions to counteract the attacks on confidentiality, integrity, authentication, and availability of security services in the Internet of Things environment and identified the two key management schemes, that is, identity and threshold schemes for Internet of Things, to resolve Internet of Things key management issues and maximum possible security services effective implementation. We evaluate our scheme with the help of mathematical and statistical techniques. (shrink)

Generally toxic employees are under performers, yet some get better salaries and excel at workplace, getting positioned at higher ranks. This research assesses the relationship between the dark triad (Narcissism, Machiavellianism, and Psychopathy) and perceived victimization with a focus on the mediating effect of abusive supervision and the moderating effect of mindfulness. The data were gathered in three waves. Both the structural equation model with partial least square and Process were used to analyze the data. The study findings suggest that (...) abusive supervision plays a mediating role in the association between the dark triad and perceived victimization. However, the results did not support the mediating role of abusive supervision in the association between narcissism and perceived victimization. Moreover, the findings suggest that mindfulness weakens the effect of abusive supervision on perceived victimization. Furthermore, our findings support the mediated-moderation model. Theoretical and practical implications of the results are also discussed. (shrink)

In this paper, we utilized triangular conorms. The essence of using S-norm is that the similarity order does not change using different norms. In fact, we are investigating for a new conception for calculating the similarity of two Fermatean fuzzy sets. For this purpose, utilizing an S-norm, we first present a formula for calculating the similarity of two Fermatean fuzzy values, so that they are truthful in similarity properties. Following that, we generalize a formula for calculating the similarity of the (...) two Fermatean fuzzy sets which prove truthful in similarity conditions. Finally, various numerical examples have been presented to elaborate this method. (shrink)

PurposeThis study aimed to apply “multi-criteria decision approach and attitude-change theory” to examine post-COVID-19 impact on entrepreneurial mindset by investigating the link between entrepreneurs social capital and entrepreneurial success. Specifically, this study analyzed entrepreneurs' dispositional factor as an underlying mechanism to bridge trust and entrepreneurial success. Furthermore, it also analyzed entrepreneurs' situational factor as boundary condition.Design/methodology/approachWe applied time-lagged data collection from 505 industrial entrepreneurs. Survey method was used for data collection. A 7-point Likert scale was used for the respondent response. (...) Hayes developed PROCESS models 4 and 7 were used to test the hypothesis.FindingsThe direct impact of trust on three elements of the ecosystem was found significantly positive on both startup behavior and entrepreneurial success. The direct impact of startup behavior on entrepreneurial success is also significantly positive. The impact of startup behavior on indirect mediation between trust and entrepreneurial success is visibly positive. The moderated and moderated mediation impact of entrepreneurial strategy found positively significant at low and medium values. However, this study found an insignificant moderated impact at high values of entrepreneurial strategy between trust on media and startup behavior. Furthermore, this study also found insignificant moderated mediation impact at high values of entrepreneurial strategy by interacting with two elements of ecosystem through startup behavior on entrepreneurial success.Originality/valueThe authors suggested that startup behavior is an underlying mechanism through which industrial entrepreneurs trust achieved desired entrepreneurial success. The authors also suggested that the influencing role of “low level of entrepreneurial strategy” in comparison with “high level entrepreneurial strategy” is more helpful to achieve entrepreneurial success.ImplicationsThis study contributed to the literature on entrepreneurial strategy for its conditional indirect moderated impact on startup behavior and moderated mediation impact on firm entrepreneurial success. It also contributed to owners of the manufacturing industry for their startup behavior as an underlying mechanism through which trust influences entrepreneurial success. (shrink)

The purpose of this research is to highlight the relationship between green product attributes and consumer trust that influence consumers’ decision to purchase green products in the context of Pakistan. This study contributes to determining quantitatively how green product attributes such as physical, perceptual, and reflexive attributes influence consumers’ trust to purchase a green product and investigates the mediating role of green marketing. Data was collected from different industrial sectors through a survey questionnaire. We employed Structural Equation Modeling using the (...) SMART-PLS software to check the reliability and validity of the constructs, and to test the hypotheses. This study reveals variations in terms of shaping the sustainable consumers’ buying behavior by modifying product attributes and green marketing strategies that are in congruence with the proposed hypotheses of this study. In the end, the findings and interpretations of the results are given which can guide the managers to develop effective green marketing campaigns in reshaping the purchase intentions of consumers toward their green products. (shrink)

Healthcare workers in Pakistan are still fighting at the frontline to control the spread of severe acute respiratory syndrome coronavirus-2 and have been identified as the earliest beneficiaries for COVID-19 vaccination by the health authorities of the country. Besides, the high vaccination rates of frontline healthcare workers are essential to overcome the ongoing pandemic and reduce the vaccines hesitancy among the general population. The current research employed the theory of planned behavior to investigate the COVID-19 vaccination behavior among FHWs in (...) Pakistan as well as the predictors of such behavior. Following the epidemic control and prevention policies, a sample of 680 FHWs were accessed to fill in the questionnaire evaluating the components of the TPB. Moreover, the potential role of anticipated regret and perceived susceptibility on COVID-19 vaccination behavior was also assessed. The partial least square structural equation modeling results revealed that the TPB components, as well as the AR, have positive associations with the COVID-19 vaccination behavior. The results further confirmed that PS positively affects the anticipated regret, attitude, and subjective norm to vaccinate against SARS-CoV-2. The perceived susceptibility also has a positive association with COVID-19 vaccination behavior through the mediation of anticipated regret, ATT, and SN. Our findings highlighted the importance of COVID-19 vaccination among healthcare workers, which can be applied to reduce vaccine hesitancy among the general public. (shrink)

This research explores the effect of servant leadership on prosocial rule-breaking (PSRB) and the mediating mechanism of public service motivation (PSM) between the association of servant leadership and PSRB. The said phenomenon is examined in the civil service context of Pakistan during the continuing crises of the COVID-19 pandemic, a situation where the traditional civil service policy and rule system has become highly complicated for passionate employees’ service performance and efficiency, and where servant leadership has received greater attention for inspiring (...) the attitudinal and behavioral outcomes of frontline workers during the pandemic. Data were collected from 546 frontline workers of the corona relief tiger force. The findings of the study revealed that servant leadership has a significant effect on PSRB and PSM, and that PSM significantly promotes PSRB. The results also revealed that servant leadership has a significant impact on PSRBviaengendering PSM. (shrink)

Web search engines usually keep users’ profiles for multiple purposes, such as result ranking and relevancy, market research, and targeted advertisements. However, user web search history may contain sensitive and private information about the user, such as health condition, personal interests, and affiliations that may infringe users’ privacy since a user’s identity may be exposed and misused by third parties. Numerous techniques are available to address privacy infringement, including Private Information Retrieval protocols that use peer nodes to preserve privacy. Previously, (...) we have proved that PIR protocols are vulnerable to the QuPiD Attack. In this research, we proposed NN-QuPiD Attack, an improved version of QuPiD Attack that uses an Artificial Neural Network based model to associate queries with their original users. The results show that the NN-QuPiD Attack gave 0.512 Recall with the Precision of 0.923, whereas simple QuPiD Attack gave 0.49 Recall with the Precision of 0.934 with the same data. (shrink)